Hydrogen wettability of clays: Implications for underground hydrogen storage

This study investigates the ability of hydrogen (H₂) to wet clay surfaces in the presence of brine, with implications for underground hydrogen storage in clay-containing reservoirs. Rather than measuring contact angles directly with hydrogen gas, a suite of other gases (carbon dioxide (CO₂), argon (Ar), nitrogen (N₂), and helium (He)) were employed in the gas-brine-clay system under storage conditions (moderate temperature (333 K) and high pressures (5, 10, 15, and 20 MPa)), characteristic of a subsurface environment with a shallow geothermal gradient. By virtue of analogies to H₂ and empirical correlations, wettabilities of hydrogen on three clay surfaces were mathematically derived and interpreted. The three clays were kaolinite, illite, and montmorillonite and represent 1:1, 2:1 non-expansive, and 2:1 expansive clay groups, respectively. All clays showed water-wetting behaviour with contact angles below 40° under all experimental set-ups. It follows that the presence of clays in the reservoir (or caprock) is conducive to capillary and/or residual trapping of the gas. Another positive inference is that any tested gas, particularly nitrogen, is suitable as cushion gas to maintain formation pressure during hydrogen storage because they all turned out to be more gas-wetting than hydrogen on the clay surfaces; this allows easier displacement and/or retrieval of hydrogen during injection/production. One downside of the predominant water wettability of the clays is the upstaged role of biogeochemical reactions at the wetted brine-clay/silicate interface and their potential to affect porosity and permeability. Water-wetting decreased from kaolinite as most water-wetting clay over illite to montmorillonite as most hydrogen-wetting clay. Their wetting behaviour is consistent with molecular dynamic modelling that establishes that the accessible basal plane of kaolinite's octahedral sheet is highly hydrophilic and enables strong hydrogen bonds whereas the same octahedral sheet in illite and montmorillonite is not accessible to the brine, rendering these clays less water-wetting.     

Usability of a cloud-based collaborative learning framework to improve learners’ experience

Computer-Supported Collaborative Learning (CSCL) is concerned with how Information and Communication Technology (ICT) might facilitate learning in groups which can be co-located or distributed over a network of computers such as Internet. CSCL supports effective learning by means of communication of ideas and information among learners, collaborative access of essential documents, and feedback from instructors and peers on learning activities. As the cloud technologies are increasingly becoming popular and collaborative learning is evolving, new directions for development of collaborative learning tools deployed on cloud are proposed. Development of such learning tools requires access to substantial data stored in the cloud. Ensuring efficient access to such data is hindered by the high latencies of wide-area networks underlying the cloud infrastructures. To improve learners’ experience by accelerating data access, important files can be replicated so a group of learners can access data from nearby locations. Since a cloud environment is highly dynamic, resource availability, network latency, and learner requests may change. In this paper, we present the advantages of collaborative learning and focus on the importance of data replication in the design of such a dynamic cloud-based system that a collaborative learning portal uses. To this end, we introduce a highly distributed replication technique that determines optimal data locations to improve access performance by minimizing replication overhead (access and update). The problem is formulated using dynamic programming. Experimental results demonstrate the usefulness of the proposed collaborative learning system used by institutions in geographically distributed locations.     

Two-agent two-machine flowshop scheduling with learning effects to minimize the total completion time

We study a two-agent scheduling problem in a two-machine permutation flowshop with learning effects. The objective is to minimize the total completion time of the jobs from one agent, given that the maximum tardiness of the jobs from the other agent cannot exceed a bound. We provide a branch-and-bound algorithm for the problem. In addition, we present several genetic algorithms to obtain near-optimal solutions. Computational results indicate that the algorithms perform well in either solving the problem or efficiently generating near-optimal solutions.     

Design of disturbance observer based on adaptive-neural control for large-scale time-delay systems in the presence of actuator fault and unknown dead zone

This article presents an adaptive neural compensation scheme for a class of large-scale time delay nonlinear systems in the presence of unknown dead zone, external disturbances, and actuator faults. In this article, the quadratic Lyapunov–Krasovskii functionals are introduced to tackle the system delays. The unknown functions of the system are estimated by using radial basis function neural networks. Furthermore, a disturbance observer is developed to approximate the external disturbances. The proposed adaptive neural compensation control method is constructed by utilizing a backstepping technique. The boundedness of all the closed-loop signals is guaranteed via Lyapunov analysis and the tracking errors are proved to converge to a small neighborhood of the origin. Simulation results are provided to illustrate the effectiveness of the proposed control approach.     

Delay compensated control of the Stefan problem and robustness to delay mismatch

This paper presents a control design for the one‐phase Stefan problem under actuator delay via a backstepping method. The Stefan problem represents a liquid‐solid phase change phenomenon which describes the time evolution of a material's temperature profile and the interface position. The actuator delay is modeled by a first‐order hyperbolic partial differential equation (PDE), resulting in a cascaded transport‐diffusion PDE system defined on a time‐varying spatial domain described by an ordinary differential equation (ODE). Two nonlinear backstepping transformations are utilized for the control design. The setpoint restriction is given to guarantee a physical constraint on the proposed controller for the melting process. This constraint ensures the exponential convergence of the moving interface to a setpoint and the exponential stability of the temperature equilibrium profile and the delayed controller in the norm. Furthermore, robustness analysis with respect to the delay mismatch between the plant and the controller is studied, which provides analogous results to the exact compensation by restricting the control gain.     

Real‐time monitoring by proton relaxometry of radical polymerization reactions of acrylamide in aqueous solution

The potential of time‐domain nuclear magnetic resonance (TD‐NMR) for the real‐time monitoring of solution radical polymerizations is demonstrated. A model system composed of a redox‐pair initiator system, acrylamide as monomer and water as solvent was investigated. A second‐generation continuous wave free precession technique was employed to measure the longitudinal relaxation time constant (T₁) of the samples throughout the polymerization reactions. This parameter was shown to be sensitive to the reactant feed free‐radical enhancement of the water molecule relaxation time, making it a good probe to monitor monomer conversion in real time in an automated, non‐destructive fashion. It was found that the T₁ value was better than the transverse relaxation time constant (T₂) for describing the evolution of the polymerization reactions, due to its greater sensitivity to paramagnetic effects. The TD‐NMR signal variation observed was linked to the formation, propagation and termination steps of the radical polymerization kinetics scheme. These first results may contribute to the application of real‐time monitoring of radical polymerization reactions employing low‐cost and robust TD‐NMR spectrometers. © 2018 Society of Chemical Industry     

Development of New Product: Rambutan Pulpy Juice

This study aimed to know the effect of adding pulp in rambutan fruit juice on the characteristics of rambutan juice during storage. Research using the CRD, the treatment were kind of pulp (mandarin and rambutan) and pulp concentration (5%, 7.5%, and 10%). The results showed that the addition of pulp significantly affect the characteristics of rambutan juice (pH, vitamin C, total acid) during storage. Pulpy juice with the most prefered was addition of rambutan pulp as much as 7.5% (w/v) and the addition of citrus pulp as much as 7.5% (w/v) with the score of 3-4 (moderate like - like).     

Extended preservation of raw beef and pork meat by hyperbaric storage at room temperature

Hyperbaric storage (HS) was evaluated as a new food preservation methodology at room temperature (RT) for beef and pork meat, both minced and in pieces, and compared to refrigeration (RF) storage. The meat samples were stored at 50, 75 and 100 MPa and variable RT up to 60 days. HS at 75 and 100 MPa could not only inhibit microbial growth but also inactivate microorganisms. Regarding physicochemical analyses, an overall equal to better pH maintenance in HS samples was achieved, and similar colour differences between HS and RF were observed. Generally, similarities in moisture content and drip loss between HS (mostly 75 and 100 MPa) and RF were detected (tendency for lower values in the former and higher values in the latter for the higher pressure level). Protein solubility revealed a decrease of sarcoplasmic protein values during storage with a pressure level dependency in some samples.     

Effect of stoichiometry and Cu-substitution on the phase structure and hydrogen storage properties of Ml-Mg-Ni-based alloys

To improve the electrochemical properties of rare-earth–Mg–Ni-based hydrogen storage alloys, the effects of stoichiometry and Cu-substitution on the phase structure and thermodynamic properties of the ...     

Nb和时效时间对热轧中锰TRIP钢中P偏聚的影响

热轧态中锰TRIP钢首先经650 ℃退火2 h,随后在550 ℃进行等温时效热处理,采用场发射扫描电镜(FE-SEM)研究该钢中P的偏聚和时效析出行为的变化情况。结果表明,中锰TRIP钢中P在晶界的偏聚是一种非平衡偏聚现象,临界时间约为50 h,与理论计算结果48 h较为吻合。在局部偏聚区域内,C与P存在共偏聚的关系,即P偏聚量高的地方,C含量也高。而合金元素Nb具有抑制P偏聚的效果,在20~70 h时效时间内,可以相对降低6.57%~19.5%的最大P偏聚量。根据电子背散射衍射(EBSD)菊池线分析,P偏聚量低于2.28at%时,P为固溶状态,高于2.28at.%时,P为析出状态。